Client Beamforming for Rate Scalability of MU-MIMO Networks

Author

Yu, Hang

Date

2015-04-24

Advisor

Zhong, Lin

Degree

Doctor of Philosophy

Abstract

The multi-user MIMO (MU-MIMO) technology allows an AP with multiple antennas to simultaneously serve multiple clients to improve the network capacity. To achieve this, the AP leverages zero-forcing beamforming (ZFBF) to eliminate the intra-cell interference between served clients. However, current MU-MIMO networks suffer from two fundamental problems that limit the network capacity. First, for a single MU-MIMO cell, as the number of clients approaches the number of antennas on the AP, the cell capacity often flattens and may even drop. Second, for multiple MU-MIMO cells, the multiple APs cannot simultaneously serve their clients due to inter-cell interference, so that the concurrent streams are constrained to a single cell with limited network capacity. Our unique perspective to tackle these two problems is that modern mobile clients can be equipped with multiple antennas for beamforming. We have proposed two solutions that leverage the client antennas. For the capacity scalability problem in a single MU-MIMO cell, we use multiple client antennas to improve the orthogonality between the channel vectors of the clients. The orthogonality between clients’ channels determines the SNR reduction from the zero-forcing beamforming by the AP, and is therefore critical for the capacity of a MU-MIMO cell to become more scalable to the number of clients. We have devised a 802.11ac-based protocol called MACCO, in which each client locally optimizes its beamforming weights based on the channel knowledge obtained from overhearing other clients’ channel reports. For the inter-cell interference problem in multiple MU-MIMO cells, we leverage multiple client antennas to assist the interfering APs to coordinately cancel the inter-cell interference between them. To achieve such coordinated interference cancellation in a practical way, We have proposed a two-step optimization including antenna usage optimization and beamforming weight optimization. We have devised another 802.11ac-based protocol called CoaCa, which integrates this two-step optimization into 802.11ac with small modifications and negligible overhead, allowing each AP and client to locally identify the optimal beamforming weights. We have implemented both MACCO and CoaCa on the WARP SDR platform leveraging the WARPLab framework, and experimentally evaluated their performance under real-world indoor wireless channels. The results have demonstrated the effectiveness of MACCO and CoaCa toward solving the capacity scalability and inter-cell interference problems of MU-MIMO networks. First, on average MACCO can increase the capacity of a single MU-MIMO cell with eight AP antennas and eight clients by 35%, compared to existing solutions that use client antennas differently. Second, for a MU-MIMO network with two cells, by cancelling the inter-cell interference CoaCa can convert the majority of the number of streams increase (50%-67%) into network capacity improvement (41%-52%).